A Systematic Review of Real-Time Medical Simulations with Soft-Tissue Deformation: Computational Approaches, Interaction Devices, System Architectures, and Clinical Validations.

Tan-Nhu Nguyen,Tien-Tuan Dao,Marie-Christine Ho Ba Tho

doi:10.1155/2020/5039329

Abstract

Simulating deformations of soft tissues is a complex engineering task, and it is even more difficult when facing the constraint between computation speed and system accuracy. However, literature lacks of a holistic review of all necessary aspects (computational approaches, interaction devices, system architectures, and clinical validations) for developing an effective system of soft-tissue simulations. This paper summarizes and analyses recent achievements of resolving these issues to estimate general trends and weakness for future developments. A systematic review process was conducted using the PRISMA protocol with three reliable scientific search engines (ScienceDirect, PubMed, and IEEE). Fifty-five relevant papers were finally selected and included into the review process, and a quality assessment procedure was also performed on them. The computational approaches were categorized into mesh, meshfree, and hybrid approaches. The interaction devices concerned about combination between virtual surgical instruments and force-feedback devices, 3D scanners, biomechanical sensors, human interface devices, 3D viewers, and 2D/3D optical cameras. System architectures were analysed based on the concepts of system execution schemes and system frameworks. In particular, system execution schemes included distribution-based, multithread-based, and multimodel-based executions. System frameworks are grouped into the input and output interaction frameworks, the graphic interaction frameworks, the modelling frameworks, and the hybrid frameworks. Clinical validation procedures are ordered as three levels: geometrical validation, model behavior validation, and user acceptability/safety validation. The present review paper provides useful information to characterize how real-time medical simulation systems with soft-tissue deformations have been developed. By clearly analysing advantages and drawbacks in each system development aspect, this review can be used as a reference guideline for developing systems of soft-tissue simulations.

Highlights

In a human body, tissues are commonly classified into hard and soft tissues
Algorithm accuracy quantifies the correctness of an implemented computational process in relation to the true process. Note that these accuracies should be within the clinically acceptable accuracy bounds for each medical application. To realistically simulate both geometric deformations and mechanical behaviors of soft tissues within a medical simulation system, computation speed must be in real time [1], and the system accuracy must be within a desired tolerance level according to each medical application
Over 80% of articles modelled the tissue physical characteristics in the methods while the others just focused on soft-tissue deformations

Summary

Introduction

Tissues are commonly classified into hard and soft tissues. While hard tissues do not deform during the motions of human bodies, soft tissues always deform when interacting with themselves, other tissues, and surgical tools. Effective integration of soft-tissue deformation behaviors into medical simulation systems has faced two constraints relating to computation speed (or computation time) and system accuracy. To realistically simulate both geometric deformations and mechanical behaviors of soft tissues within a medical simulation system, computation speed must be in real time [1], and the system accuracy must be within a desired tolerance level according to each medical application. It is important to note that real time is one of the most important requirements for clinical applications, most softtissue simulation systems hardly satisfied both acceptable model accuracy and real-time computation speed [4]. Most simulation systems with soft-tissue deformations hardly satisfy real-time requirements [8], and they cannot both correctly compute soft-tissue deformations and effectively achieve real-time computation speeds [7]. Despite this hard constraint, numerous strategies have been developed for improving both computation speed and accuracy of soft-tissue simulation systems

Methods

Results

Discussion

Conclusion